Search Results

You are looking at 1 - 2 of 2 items for

  • Author or Editor: Rafael Montanari x
Clear All Modify Search
Open access

Job Teixeira de Oliveira, Rubens Alves de Oliveira, Mario Puiatti, Paulo Teodoro and Rafael Montanari

The objective of this study was to evaluate whether the spatial variability of plant production components and the use of an irrigation and fertirrigation management system with controlled deficit affect the yield and incidence of garlic lateral shoot growing (LSG). An analysis of these data through statistical and geostatistical techniques made it possible to verify that the increase in yield is directly related to the height and diameter of the bulb and that the lateral shoot growing is directly related to the increase in yield. Lower water depths and lower nitrogen doses applied during clove differentiation imply a lower incidence of LSG, whereas increased irrigation and fertigation with nitrogen results in lower bulb volumes.

Open access

Job Teixeira de Oliveira, Rubens Alves de Oliveira, Lucas Allan Almeida Oliveira, Paulo Teodoro and Rafael Montanari

Among the crops that are usually grown under irrigation, one can mention garlic, which is a product with high demand in Brazil and the world, it is highly valued in the cuisine of several countries, and is an aggregated crop with high economic value. In 2018, this work was conducted in Yellow Red Latosol. The objective was to characterize the structure and magnitude of the spatial distribution of garlic production components and to map the productive components to visualize spatial distribution and to evaluate the spatial correlation between garlic bulb yield (BY) and other variables of the crop: total plant mass (TPM), number of leaves (NL), floral tassel length (FTL), leaf length (LL), leaf width (LW), pseudostem diameter (PD), shoot wet mass (SWM), shoot dry mass (SDM), number of cloves per bulb (NCB), clove mass (CM), root dry mass (RDM), and irrigation (IRR). All these traits were sampled in a 90-point grid georeferenced. Data analysis using statistical and geostatistical techniques made it possible to verify that the production components and BY, TPM, NL, FTL, LL, LW, PD, SWM, SDM, CM, and IRR presented special dependence. The spatial correlation between BY and TPM, LW, and CM showed a moderate spatial dependence.